How to analyze Singapore GE2020 Voting Results
For GE2020, PAP won 83 of the 93 seats in Singapore Parliament. This meant that PAP had a super majority of 89% based on seats. Of course, this meant that they had the majority to form the government. Based on overall vote count, PAP only managed to get 61.24% of the votes. So why did they not get the other 40%? Or why did the opposition fail to get the 60%?
Singapore had its election on 10 July 2020. In the election, all the 93 seats were contested. Out of the 93 seats, 14 were single seat constituencies, meaning that there was only one candidate representing the constituency. The other 79 seats were grouped into 4 or 5 seats GRC. This meant that voters voted the group of candidates in the GRC with one single vote.
There were many analyses. Some believed that the swing was caused by young voters. Others thought that the policies by PAP needed change. Some even believed that it was the candidates who were not popular. Others mentioned that the constituencies were not well managed. All of them could be right or wrong.
How to find out the real reason(s)?
61.24% of the votes is the average. Some constituencies won more votes than others. The results for the SMC were more straightforward because it was based on one candidate against another. For GRC, the reason(s) for the win or loss was not as clear. Was it due to the minister(s) in the GRC or was it due to other factors?
Whether it was a SMC or a GRC, the results could be further analyzed. If I am to analyze the results this is what I would do.
Analyze by Polling Stations
There were 93 seats and they were divided into 14 SMCs and 17 GRCs. If we were just analyzing these 31 results, there was only so much you could do with it. You can profile the constituencies by young and old voters, income group. Profiling by constituencies would not be able to tell you much.
But if the votes count for the 93 seats were broken down into the 1,100 polling stations all over Singapore, the political parties could have an in-depth analysis. It could immediately help the candidate or the party answered this question:
Did the majority of the voters in this area for or against me?
This was possible because the polling stations were located within 500m of where the voters stayed. The candidates did not have to guess based on tens of thousand of voters. Each polling station served an average of 2,400 voters only. The stats would be a good source to learn more about your voters, create plans on how to serve your supporters and win over more supporters.
Is it minister effects?
If you were trying to analyze the results of a GRC, you could link the polling stations to the MPs that were actively serving these areas. Through this link, you would know whether that candidate truly had the support of that area or he/she was being “compensated” by other more popular member(s) in the GRC.
Linking the voting results to the polling stations could help profile the voters more accurately in terms of
- Type of housing they were staying in
- The age profile of the voters
- Family Size
These could help the candidates develop plans to win over more voters and help fine-tune their policies/manifesto to serve their supporters.
These analyses of slightly over a thousand rows do not require a sophisticated software. Simply link the voting results to the candidate and use Excel Pivot Table to analyze the results by constituency, candidate, polling station and the answer (why they won/loss the election) would become much clearer.
Further analysis could be done by comparing the results against the election in 2015. The number of polling stations of 832 was lesser than 1,100 in 2020, but I am sure some form of comparison can be generated. This comparison could help all the political parties understand where the votes had swung to/from.
Using Power Pivot, a side by side comparison of the voting results could be done between GE2015 and GE2020 and the variance could be calculated by polling station.
Business Intelligence or Analysis worked the same way as Political Intelligence/Analysis.
If you are interested to know how to analyze your business effectively, contact me for a free discussion.
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